Background screening and risk assessment platform for hiring and workforce decisions
Checkr operates a data platform for background screening and risk assessment, built on Python, Go, and Ruby with a modern cloud stack (AWS, Kubernetes, Kafka, Spark). The tech mix—data lake infrastructure (Iceberg, Athena, dbt), machine learning tooling, and API-first architecture—reflects a company moving from legacy screening workflows toward programmable, compliant decisioning at scale. Active hiring is engineering-heavy (51 roles) with senior-level focus, while projects signal product consolidation (integrating an acquired background check product) and platform modernization (replacing Looker, adopting Terraform and Istio).
Notable leadership hires: Head of Growth
Checkr provides background screening, motor vehicle reports, and criminal searches for employers, lending platforms, and workforce management. The platform uses machine learning and AI to assess risk and support hiring decisions while ensuring FCRA compliance. Customers range from national and regional lenders to ATS platforms and enterprises managing hiring workflows. The company operates a data-centric architecture—Kafka-based ingest, Spark/PySpark transformation, MongoDB and SQL storage—designed to handle high-volume screening requests and integrate with downstream hiring systems. Recent product work centers on consolidating an acquired background check product and improving customer onboarding.
Python, Ruby, Go, JavaScript/TypeScript for application code; AWS (EKS, EMR, Glue, Athena), Kubernetes, Kafka, and Spark for data and infrastructure; dbt, Iceberg, and MongoDB for storage and transformation.
United States and Chile. The majority of active roles are based in the U.S.
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